Text Classification
Transformers
TensorBoard
Safetensors
English
deberta-v2
cross-encoder
sequence-classification
text-embeddings-inference
Instructions to use xpmir/cross-encoder-DeBERTav3-DistillRankNET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xpmir/cross-encoder-DeBERTav3-DistillRankNET with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xpmir/cross-encoder-DeBERTav3-DistillRankNET")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xpmir/cross-encoder-DeBERTav3-DistillRankNET") model = AutoModelForSequenceClassification.from_pretrained("xpmir/cross-encoder-DeBERTav3-DistillRankNET") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
runs/1770814699.8654444/events.out.tfevents.1770814699.jzxh263.89186.1
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8cfd291438220cb6a5f447234d4c350a7697c5e4c46574721c5aaf81d1064b0d
|
| 3 |
+
size 4576
|
runs/events.out.tfevents.1770775898.jzxh263.89186.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:31b37310c4904ba5fba241792df2ef79c398e2fd42ad8b0e341c29e61ae75ecd
|
| 3 |
+
size 15681060
|